Synovial Fibroblast 3.1: Secretion response of seven primary human synovial fibroblast samples from healthy and rheumatoid arthritis donors to a panel of 3 stimuli and 5 small molecule inhibitors (replicate 1 of 2)
Project description:Previously, we published a dataset of human blood plasma and serum samples of 10 healthy males and 10 healthy females, fractionated on a set of sorbents (cation exchange Toyopearl CM-650M, CM Bio-Gel A, SP Sephadex C-25 and anion exchange QAE Sephadex A-25) and analyzed by LC-MS/MS individually and pooled in equal amounts (Supplementary Table S1, Sheet 1) [33]. The mass spectrometry peptidomics data was deposited to the ProteomeXchange Consortium via the PRIDE partner repository (dataset identifiers PXD008141 and 10.6019/PXD008141). Direct download link: http://www.ebi.ac.uk/pride/archive/projects/PXD008141. We analyzed this dataset again within this work. The detailed information about the dataset of blood plasma/serum samples of 20 healthy donors fractionated on a set of sorbents is available in the original paper [33], including the clinical parameters of the donors, sample collection, plasma/serum fractionation, peptide extraction and LC-MS/MS analysis. 33. Arapidi, G. et al. Peptidomics dataset: Blood plasma and serum samples of healthy donors fractionated on a set of chromatography sorbents. Data Brief 18, 1204–1211 (2018).
Project description:Previously, we published a dataset of human blood plasma and serum samples of 10 healthy males and 10 healthy females, fractionated on a set of sorbents (cation exchange Toyopearl CM-650M, CM Bio-Gel A, SP Sephadex C-25 and anion exchange QAE Sephadex A-25) and analyzed by LC-MS/MS individually and pooled in equal amounts (Supplementary Table S1, Sheet 1) [33]. We focused on those peptides that could be found in the blood plasma and serum using a standard search against the database of human proteins (UniProt Knowledgebase, taxon human). The combination of search engines MASCOT and X! Tandem, based on Scaffold 4 software with FDR less than 1%, allowed us to identify 15,530 unique peptides that belong to 2,127 protein groups (Table 1, Supplementary Table S1, Sheets 2 and 3). The Venn diagram shows that slightly less than 40% of the peptides are found in all four analyzed samples (Figures 1A and 1B). About 70% of the peptides are found in at least two samples. The accumulation diagram (Figure 1C) shows that the number of new unique peptides does not reach a plateau after repeated analyses of the same plasma sample — even after six runs. The high variability of the plasma and serum peptidome most likely indicates its sophisticated composition. 33. Arapidi, G. et al. Peptidomics dataset: Blood plasma and serum samples of healthy donors fractionated on a set of chromatography sorbents. Data Brief 18, 1204–1211 (2018).
Project description:Previously, we published a dataset of human blood plasma and serum samples of 10 healthy males and 10 healthy females, fractionated on a set of sorbents (cation exchange Toyopearl CM-650M, CM Bio-Gel A, SP Sephadex C-25 and anion exchange QAE Sephadex A-25) and analyzed by LC-MS/MS individually and pooled in equal amounts (Supplementary Table S1, Sheet 1) [33]. Blood is a complex tissue and can theoretically contain products of all processes occurring in different parts of the body. To identify potential sources of “alien” (non-human) plasma peptides, we performed a de novo analysis of mass spectrometry data. De novo analysis is a less efficient method of identification than search against databases, since the accuracy and resolution of modern mass spectrometers such as QTOF or Orbitrap remains not high enough. However, we use de novo analysis to identify organisms that include the most abundant components of the complex peptide mixture. This procedure allows us to develop a hypothesis and then perform a standard search against a database of proteins of identified organisms. The de novo identification was carried out using PEAKS Studio 8.0 (Bioinformatics Solutions Inc., Canada) and mass spectrometry driven BLAST analysis against the RefSeq non-redundant database NCBInr (https://www.ncbi.nlm.nih.gov/protein/). Mass spectra identified as fragments of proteins from different organisms were assigned to a taxonomic level at which these different organisms converged (Supplementary Table S2). 33. Arapidi, G. et al. Peptidomics dataset: Blood plasma and serum samples of healthy donors fractionated on a set of chromatography sorbents. Data Brief 18, 1204–1211 (2018).
Project description:Each of 914 cell samples either at the control condition or treated with FDA-approved cancer drugs is sequenced by the single-ended 3'-DGE mRNA-sequencing method with a read length of 46 base pairs, and a total of 914 raw sequence data files in the FASTQ format are generated. These sequence data files are then analyzed by a high-performance computational pipeline and ranked lists of gene signatures and biological processes related to drug-induced cardiotoxicity are generated for each drug. The raw sequence datasets and the analysis results have been carefully controlled for data quality, and they are made publicly available at the Gene Expression Omnibus (GEO) database repository of NIH. As such, this broad drug-stimulated transcriptomi dataset is valuable for the prediction of drug toxicities and their mitigations.
Project description:Each of 70 cell samples either at the control condition or treated with FDA-approved cancer drugs is sequenced by the single-ended random-primed mRNA-sequencing method with a read length of 100 base pairs, and a total of 70 raw sequence data files in the FASTQ format are generated. These sequence data files are then analyzed by a high-performance computational pipeline and ranked lists of gene signatures and biological processes related to drug-induced cardiotoxicity are generated for each drug. The raw sequence datasets and the analysis results have been carefully controlled for data quality, and they are made publicly available at the Gene Expression Omnibus (GEO) database repository of NIH. As such, this broad drug-stimulated transcriptomi dataset is valuable for the prediction of drug toxicities and their mitigations.
Project description:Reanalysis of three large human tissue proteomics datasets using a bespoke GENCODE database and multiOTHER algorithm high confidence pipeline.
Project description:ADP-ribosylation (ADPr) is a regulatory post-translational modification targeting nine amino acid residues, but glutamate/aspartate-linked ADPr (Glu/Asp-ADPr) is labile and remains challenging to detect using conventional mass spectrometry (MS)-based workflows. Using synthetic peptides, we show that ester-linked Glu/Asp-ADPr is lost under alkaline conditions, elevated temperatures, and by hydrolysis via wildtype Af1521. We developed an acidic enrichment workflow incorporating an Af1521 mutant that preserves Glu/Asp-ADPr, enabling site-specific, system-wide MS analysis. In cytokine-stimulated A549 and HeLa cells, we identified >600 Glu/Asp- and >200 Cys-ADPr sites. Glu/Asp-ADPr marks cytoplasmic, immune-related protein networks, contrasting with nuclear Ser-ADPr. Quantitative profiling revealed reproducible, cell type- and treatment-specific patterns. PARP10-mediated Glu/Asp ADPr of ubiquitin indicates direct crosstalk with ubiquitin signaling pathways. Interferon treatments revealed conserved antiviral PARP networks extensively modified on Glu/Asp residues. Together, our work establishes a robust MS-based workflow and provides a resource of site-specific ADPr events, revealing residue-specific ADPr in innate immune signaling.
Project description:We developed SpotLink to identify site non-specific cross-links from the proteome scale. Here described the Abeta dataset and the HeLa dataset to evaluate SpotLink.